Evaluating the Usability of a Remote Ischemic Conditioning Device for Pre-Hospital Stroke Management: Insights from Paramedic Simulations
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: In acute stroke, often-prolonged hospital transport times present an opportunity for early interventions to salvage brain tissue. Remote ischemic conditioning (RIC), where brief cycles of ischemia-reperfusion in a limb are induced to protect the brain, is a promising treatment for this setting. We assessed the usability of a novel RIC system in a simulated emergency response scenario. METHODS: Paramedics were asked to use the RIC device in an emergency stroke care and ambulance transport simulation, overseen by a confederate. Feedback on device use was collected through questionnaires, including the System Usability Scale (SUS) and the NASA Task Load Index (NASA-TLX), and a semi-structured interview. Questionnaire responses were summarized using descriptive statistics; interview transcripts were analyzed thematically. RESULTS: Nine paramedics (including the confederate) participated, with a mean of 10.0 ± 10.3 years of professional experience. Questionnaire responses indicated high device usability (mean SUS score: 85.3 ± 12.9 out of 100) and low task-related demands, effort, and frustration (mean NASA-TLX domain scores: ≤3.9 out of 20). Seven paramedics stated they would use the device in daily practice. They expressed concerns related to display screen clarity, interference with standard procedures, cable management, device fragility, and patient discomfort. Suggested improvements included adding indicators of device performance and refining the cuff design. CONCLUSIONS: While the device was considered easy to use, paramedics also identified important areas of improvement. With a small, localized study sample, our findings are primarily applicable to the refinement of the RICovery system for use in future clinical trials in the same healthcare setting. However, feedback on the importance of mitigating potential interference of newly introduced procedures with those already established, robustness of equipment, and effective paramedic-patient communication may also help inform the design of other pre-hospital interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".